Publikationen

Autor	Wilmsdorff, Julian von; Lenhart, Malte; Kirchbuchner, Florian; Kuijper, Arjan
Datum	2022
Art	Conference Paper
Abstrakt	In this extended version of the paper “Linoc: A Prototyping Platform for Capacitive and Passive Electrical Field Sensing” [15], the Linoc prototyping toolkit is presented in more detail, accompanied by evaluations and recent adaptations in research projects. Central to the Linoc Toolkit are the two capacitive and the two Electric Potential Sensing (EPS) groups, two technologies used for unobtrusive proximity detection in the field of Human Computer Interface (HCI). Important design goals in its creation were its usability and connectivity to facilitate future adaptation in research and the development of novel use cases. The usability and quality of the measurements of the Linoc prototyping toolkit were evaluated in terms of demonstration, usage and technical performance. Participants in the usage study expressed an interest for further usage, along with a fast learning curve. Technical benchmarks show a sensor range equal to its predecessors and several operational prototypes indicated its potential to be used in future projects. Consequently, first larger adaptations are presented in this paper. In addition to the presentation of the toolkit, we will also discuss the influence of the board firmware regarding noise generation and stability of the acquired capacitive and passive electric field measurements. The main focus of this investigation will be placed on peripherals of the microcontroller as well as parts of the prototyping platform that are capable of generating high frequency wave forms. These explorations of the capabilities of the toolkit are especially important for applications using the integrated Wi-Fi and Bluetooth modalities. Another complement in this extended version, is a more extensive description of the test setup used to measure the sensor performance to facilitate replication and confirmation of our results.
Konferenz	International Conference on Sensor Networks (SENSORNETS) 2020
ISBN	978-3-031-17717-0
Publisher	Springer
Url	https://publica.fraunhofer.de/handle/publica/428719